Overview

Dataset statistics

Number of variables35
Number of observations162273
Missing cells42812
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.3 MiB
Average record size in memory280.0 B

Variable types

CAT24
NUM6
BOOL4
DATE1

Warnings

horario has a high cardinality: 1302 distinct values High cardinality
km has a high cardinality: 7918 distinct values High cardinality
municipio has a high cardinality: 1767 distinct values High cardinality
marca has a high cardinality: 5555 distinct values High cardinality
latitude has a high cardinality: 37312 distinct values High cardinality
longitude has a high cardinality: 37317 distinct values High cardinality
delegacia has a high cardinality: 173 distinct values High cardinality
uop has a high cardinality: 86 distinct values High cardinality
pesid is highly correlated with id and 1 other fieldsHigh correlation
id is highly correlated with pesid and 1 other fieldsHigh correlation
id_veiculo is highly correlated with id and 1 other fieldsHigh correlation
regional is highly correlated with uf and 1 other fieldsHigh correlation
uf is highly correlated with regional and 1 other fieldsHigh correlation
uop is highly correlated with uf and 1 other fieldsHigh correlation
marca has 8151 (5.0%) missing values Missing
ano_fabricacao_veiculo has 9920 (6.1%) missing values Missing
idade has 15759 (9.7%) missing values Missing
uop has 8519 (5.2%) missing values Missing
idade is highly skewed (γ1 = 29.83797844) Skewed

Reproduction

Analysis started2020-10-08 20:58:43.504038
Analysis finished2020-10-08 21:00:05.672360
Duration1 minute and 22.17 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct67446
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean221717.4169
Minimum182210
Maximum266627
Zeros0
Zeros (%)0.0%
Memory size1.2 MiB
2020-10-08T18:00:05.908214image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum182210
5-th percentile186560.8
Q1202070
median221655
Q3241471
95-th percentile256881
Maximum266627
Range84417
Interquartile range (IQR)39401

Descriptive statistics

Standard deviation22637.1258
Coefficient of variation (CV)0.1020989966
Kurtosis-1.198925079
Mean221717.4169
Median Absolute Deviation (MAD)19699
Skewness0.008371994235
Sum3.597875039e+10
Variance512439464.4
MonotocityNot monotonic
2020-10-08T18:00:06.155060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20072874< 0.1%
 
23031162< 0.1%
 
22865956< 0.1%
 
21589455< 0.1%
 
19236852< 0.1%
 
26448251< 0.1%
 
22171051< 0.1%
 
20246050< 0.1%
 
25587449< 0.1%
 
25561449< 0.1%
 
Other values (67436)16172499.7%
 
ValueCountFrequency (%) 
1822104< 0.1%
 
1822111< 0.1%
 
1822121< 0.1%
 
1822141< 0.1%
 
1822152< 0.1%
 
ValueCountFrequency (%) 
2666271< 0.1%
 
2665731< 0.1%
 
2664342< 0.1%
 
2664063< 0.1%
 
2662552< 0.1%
 

pesid
Real number (ℝ≥0)

HIGH CORRELATION

Distinct162272
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean492648.2693
Minimum402087
Maximum594393
Zeros0
Zeros (%)0.0%
Memory size1.2 MiB
2020-10-08T18:00:06.486856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum402087
5-th percentile412353.55
Q1448657.75
median493085.5
Q3536997.25
95-th percentile571369.45
Maximum594393
Range192306
Interquartile range (IQR)88339.5

Descriptive statistics

Standard deviation51063.88098
Coefficient of variation (CV)0.1036518022
Kurtosis-1.189998552
Mean492648.2693
Median Absolute Deviation (MAD)44173
Skewness-0.01791316038
Sum7.994301996e+10
Variance2607519941
MonotocityNot monotonic
2020-10-08T18:00:06.742696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
5673801< 0.1%
 
4217831< 0.1%
 
4217881< 0.1%
 
5736461< 0.1%
 
4217871< 0.1%
 
4217861< 0.1%
 
4217851< 0.1%
 
5740121< 0.1%
 
4217841< 0.1%
 
4217821< 0.1%
 
Other values (162262)162262> 99.9%
 
ValueCountFrequency (%) 
4020871< 0.1%
 
4020921< 0.1%
 
4020931< 0.1%
 
4020941< 0.1%
 
4020951< 0.1%
 
ValueCountFrequency (%) 
5943931< 0.1%
 
5942701< 0.1%
 
5942261< 0.1%
 
5939481< 0.1%
 
5939471< 0.1%
 
Distinct365
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Minimum2019-01-01 00:00:00
Maximum2019-12-31 00:00:00
2020-10-08T18:00:07.015529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:07.274366image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

dia_semana
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
domingo
27930 
sábado
27071 
sexta-feira
25360 
segunda-feira
21902 
quinta-feira
20634 
Other values (2)
39376 
ValueCountFrequency (%) 
domingo2793017.2%
 
sábado2707116.7%
 
sexta-feira2536015.6%
 
segunda-feira2190213.5%
 
quinta-feira2063412.7%
 
terça-feira1977012.2%
 
quarta-feira1960612.1%
 
2020-10-08T18:00:07.796040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:07.939952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:08.251759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length11
Mean length9.995328859
Min length6

horario
Categorical

HIGH CARDINALITY

Distinct1302
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
18:30:00
 
2414
19:00:00
 
2400
18:00:00
 
2283
17:00:00
 
1870
19:30:00
 
1868
Other values (1297)
151438 
ValueCountFrequency (%) 
18:30:0024141.5%
 
19:00:0024001.5%
 
18:00:0022831.4%
 
17:00:0018701.2%
 
19:30:0018681.2%
 
16:00:0017551.1%
 
17:30:0016821.0%
 
16:30:0016761.0%
 
07:00:0015861.0%
 
07:30:0015661.0%
 
Other values (1292)14317388.2%
 
2020-10-08T18:00:08.512596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique79 ?
Unique (%)< 0.1%
2020-10-08T18:00:08.753445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length8
Mean length8
Min length8

uf
Categorical

HIGH CORRELATION

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
MG
21380 
SC
19574 
PR
18259 
RS
11425 
RJ
10889 
Other values (22)
80746 
ValueCountFrequency (%) 
MG2138013.2%
 
SC1957412.1%
 
PR1825911.3%
 
RS114257.0%
 
RJ108896.7%
 
SP102236.3%
 
BA88885.5%
 
GO80405.0%
 
ES65814.1%
 
PE64053.9%
 
Other values (17)4060925.0%
 
2020-10-08T18:00:08.979307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:09.196172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

br
Real number (ℝ≥0)

Distinct115
Distinct (%)0.1%
Missing231
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean217.4679713
Minimum10
Maximum495
Zeros0
Zeros (%)0.0%
Memory size1.2 MiB
2020-10-08T18:00:09.414035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile40
Q1101
median163
Q3354
95-th percentile470
Maximum495
Range485
Interquartile range (IQR)253

Descriptive statistics

Standard deviation132.0509173
Coefficient of variation (CV)0.6072200724
Kurtosis-1.16223415
Mean217.4679713
Median Absolute Deviation (MAD)99
Skewness0.3898102809
Sum35238945
Variance17437.44475
MonotocityNot monotonic
2020-10-08T18:00:09.655884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1012598916.0%
 
1162241713.8%
 
38179854.9%
 
4078104.8%
 
15364164.0%
 
36454243.3%
 
16348943.0%
 
27747032.9%
 
47045952.8%
 
26244272.7%
 
Other values (105)6738241.5%
 
ValueCountFrequency (%) 
109610.6%
 
2024271.5%
 
3014< 0.1%
 
4078104.8%
 
5014520.9%
 
ValueCountFrequency (%) 
49541< 0.1%
 
4936240.4%
 
48865< 0.1%
 
48752< 0.1%
 
4842< 0.1%
 

km
Categorical

HIGH CARDINALITY

Distinct7918
Distinct (%)4.9%
Missing231
Missing (%)0.1%
Memory size1.2 MiB
1
 
746
3
 
665
2
 
604
5
 
544
4
 
525
Other values (7913)
158958 
ValueCountFrequency (%) 
17460.5%
 
36650.4%
 
26040.4%
 
55440.3%
 
45250.3%
 
64080.3%
 
73540.2%
 
173450.2%
 
93200.2%
 
83170.2%
 
Other values (7908)15721496.9%
 
2020-10-08T18:00:09.958695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique459 ?
Unique (%)0.3%
2020-10-08T18:00:10.215537image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length3
Mean length3.657422985
Min length1

municipio
Categorical

HIGH CARDINALITY

Distinct1767
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
BRASILIA
 
2727
CURITIBA
 
2514
SAO JOSE
 
1839
GUARULHOS
 
1711
SERRA
 
1492
Other values (1762)
151990 
ValueCountFrequency (%) 
BRASILIA27271.7%
 
CURITIBA25141.5%
 
SAO JOSE18391.1%
 
GUARULHOS17111.1%
 
SERRA14920.9%
 
PALHOCA13600.8%
 
DUQUE DE CAXIAS13570.8%
 
BETIM12240.8%
 
PORTO VELHO11370.7%
 
TERESINA10720.7%
 
Other values (1757)14584089.9%
 
2020-10-08T18:00:10.479374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique34 ?
Unique (%)< 0.1%
2020-10-08T18:00:10.744209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length9
Mean length10.59797995
Min length3

causa_acidente
Categorical

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Falta de Atenção à Condução
60672 
Desobediência às normas de trânsito pelo condutor
22239 
Velocidade Incompatível
13370 
Ingestão de Álcool
12646 
Não guardar distância de segurança
12206 
Other values (19)
41140 
ValueCountFrequency (%) 
Falta de Atenção à Condução6067237.4%
 
Desobediência às normas de trânsito pelo condutor2223913.7%
 
Velocidade Incompatível133708.2%
 
Ingestão de Álcool126467.8%
 
Não guardar distância de segurança122067.5%
 
Defeito Mecânico no Veículo72524.5%
 
Condutor Dormindo55823.4%
 
Falta de Atenção do Pedestre46512.9%
 
Pista Escorregadia45352.8%
 
Ultrapassagem Indevida39252.4%
 
Other values (14)151959.4%
 
2020-10-08T18:00:10.990056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:11.242899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length78
Median length27
Mean length29.02841508
Min length10

tipo_acidente
Categorical

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Colisão traseira
38070 
Colisão transversal
23753 
Colisão lateral
22902 
Saída de leito carroçável
19582 
Colisão frontal
15344 
Other values (11)
42622 
ValueCountFrequency (%) 
Colisão traseira3807023.5%
 
Colisão transversal2375314.6%
 
Colisão lateral2290214.1%
 
Saída de leito carroçável1958212.1%
 
Colisão frontal153449.5%
 
Atropelamento de Pedestre81475.0%
 
Colisão com objeto estático78934.9%
 
Tombamento74634.6%
 
Queda de ocupante de veículo48613.0%
 
Engavetamento45802.8%
 
Other values (6)96786.0%
 
2020-10-08T18:00:11.538713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:11.779566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length31
Median length16
Mean length18.23035872
Min length8
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Com Vítimas Feridas
125176 
Sem Vítimas
22154 
Com Vítimas Fatais
14943 
ValueCountFrequency (%) 
Com Vítimas Feridas12517677.1%
 
Sem Vítimas2215413.7%
 
Com Vítimas Fatais149439.2%
 
2020-10-08T18:00:12.002426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:12.148337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:12.349212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length19
Mean length17.81573028
Min length11

fase_dia
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Pleno dia
89463 
Plena Noite
55834 
Anoitecer
9345 
Amanhecer
 
7631
ValueCountFrequency (%) 
Pleno dia8946355.1%
 
Plena Noite5583434.4%
 
Anoitecer93455.8%
 
Amanhecer76314.7%
 
2020-10-08T18:00:12.582066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:12.715984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:12.927852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length9
Mean length9.688148984
Min length9

sentido_via
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Crescente
87052 
Decrescente
74990 
Não Informado
 
231
ValueCountFrequency (%) 
Crescente8705253.6%
 
Decrescente7499046.2%
 
Não Informado2310.1%
 
2020-10-08T18:00:13.156707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:13.295623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:13.482507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length9
Mean length9.929939053
Min length9
Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Céu Claro
94822 
Nublado
27464 
Chuva
17510 
Sol
12956 
Garoa/Chuvisco
 
5535
Other values (5)
 
3986
ValueCountFrequency (%) 
Céu Claro9482258.4%
 
Nublado2746416.9%
 
Chuva1751010.8%
 
Sol129568.0%
 
Garoa/Chuvisco55353.4%
 
Ignorado21261.3%
 
Nevoeiro/Neblina15250.9%
 
Vento3270.2%
 
Granizo7< 0.1%
 
Neve1< 0.1%
 
2020-10-08T18:00:13.703370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-10-08T18:00:13.846280image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:14.206055image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length16
Median length9
Mean length7.965896976
Min length3

tipo_pista
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Simples
85939 
Dupla
63688 
Múltipla
12646 
ValueCountFrequency (%) 
Simples8593953.0%
 
Dupla6368839.2%
 
Múltipla126467.8%
 
2020-10-08T18:00:14.430918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:14.602812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:14.801687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length7
Mean length6.29298158
Min length5

tracado_via
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Reta
101632 
Curva
22973 
Não Informado
18373 
Interseção de vias
 
8132
Desvio Temporário
 
4268
Other values (5)
 
6895
ValueCountFrequency (%) 
Reta10163262.6%
 
Curva2297314.2%
 
Não Informado1837311.3%
 
Interseção de vias81325.0%
 
Desvio Temporário42682.6%
 
Rotatória29931.8%
 
Retorno Regulamentado18361.1%
 
Viaduto10080.6%
 
Ponte9010.6%
 
Túnel1570.1%
 
2020-10-08T18:00:15.023547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:15.205434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:15.570210image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length21
Median length4
Mean length6.513794655
Min length4

uso_solo
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Não
90021 
Sim
72252 
ValueCountFrequency (%) 
Não9002155.5%
 
Sim7225244.5%
 
2020-10-08T18:00:15.800067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:15.943975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:16.101877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

id_veiculo
Real number (ℝ≥0)

HIGH CORRELATION

Distinct112051
Distinct (%)69.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean395616.163
Minimum324863
Maximum475775
Zeros0
Zeros (%)0.0%
Memory size1.2 MiB
2020-10-08T18:00:16.371711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum324863
5-th percentile331763
Q1360260
median395854
Q3431382
95-th percentile458651
Maximum475775
Range150912
Interquartile range (IQR)71122

Descriptive statistics

Standard deviation40807.36381
Coefficient of variation (CV)0.1031488792
Kurtosis-1.203031293
Mean395616.163
Median Absolute Deviation (MAD)35559
Skewness-0.008449811909
Sum6.419782162e+10
Variance1665240941
MonotocityNot monotonic
2020-10-08T18:00:16.608564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
41150662< 0.1%
 
38512254< 0.1%
 
41002854< 0.1%
 
34224252< 0.1%
 
39592051< 0.1%
 
36086750< 0.1%
 
47178050< 0.1%
 
45676948< 0.1%
 
45629847< 0.1%
 
44058447< 0.1%
 
Other values (112041)16175899.7%
 
ValueCountFrequency (%) 
3248631< 0.1%
 
3248681< 0.1%
 
3248712< 0.1%
 
3248722< 0.1%
 
3248751< 0.1%
 
ValueCountFrequency (%) 
4757751< 0.1%
 
4756801< 0.1%
 
4754161< 0.1%
 
4754151< 0.1%
 
4753721< 0.1%
 

tipo_veiculo
Categorical

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Automóvel
70650 
Motocicleta
31858 
Caminhonete
14228 
Caminhão-trator
12068 
Caminhão
11517 
Other values (19)
21952 
ValueCountFrequency (%) 
Automóvel7065043.5%
 
Motocicleta3185819.6%
 
Caminhonete142288.8%
 
Caminhão-trator120687.4%
 
Caminhão115177.1%
 
Ônibus70544.3%
 
Camioneta41602.6%
 
Motoneta37462.3%
 
Bicicleta20861.3%
 
Utilitário19001.2%
 
Other values (14)30061.9%
 
2020-10-08T18:00:16.916373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-10-08T18:00:17.171212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length9
Mean length9.828326339
Min length6

marca
Categorical

HIGH CARDINALITY
MISSING

Distinct5555
Distinct (%)3.6%
Missing8151
Missing (%)5.0%
Memory size1.2 MiB
VW/GOL 1.0
 
1984
HONDA/CG 125 FAN KS
 
1673
HONDA/CG 150 TITAN KS
 
1543
MBENZ/MPOLO PARADISO R
 
1508
HONDA/CG 150 FAN ESI
 
1353
Other values (5550)
146061 
ValueCountFrequency (%) 
VW/GOL 1.019841.2%
 
HONDA/CG 125 FAN KS16731.0%
 
HONDA/CG 150 TITAN KS15431.0%
 
MBENZ/MPOLO PARADISO R15080.9%
 
HONDA/CG 150 FAN ESI13530.8%
 
HONDA/BIZ 125 ES12500.8%
 
HONDA/CG150 FAN ESDI12020.7%
 
HONDA/CG 150 TITAN ESD9690.6%
 
HONDA/CB 300R9540.6%
 
HONDA/CG 125 FAN9320.6%
 
Other values (5545)14075486.7%
 
(Missing)81515.0%
 
2020-10-08T18:00:17.459033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1209 ?
Unique (%)0.8%
2020-10-08T18:00:17.719874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length25
Median length19
Mean length17.95007796
Min length3

ano_fabricacao_veiculo
Real number (ℝ≥0)

MISSING

Distinct63
Distinct (%)< 0.1%
Missing9920
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean2009.417799
Minimum1900
Maximum2019
Zeros0
Zeros (%)0.0%
Memory size1.2 MiB
2020-10-08T18:00:17.938737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile1995
Q12007
median2011
Q32014
95-th percentile2018
Maximum2019
Range119
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.536433426
Coefficient of variation (CV)0.003750555722
Kurtosis7.773418505
Mean2009.417799
Median Absolute Deviation (MAD)4
Skewness-1.823216284
Sum306140830
Variance56.79782879
MonotocityNot monotonic
2020-10-08T18:00:18.196575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2013120487.4%
 
2011118197.3%
 
2018108526.7%
 
2014108276.7%
 
2012103856.4%
 
2010102826.3%
 
200884035.2%
 
200979664.9%
 
201575854.7%
 
201774994.6%
 
Other values (53)5468733.7%
 
(Missing)99206.1%
 
ValueCountFrequency (%) 
190015< 0.1%
 
19511< 0.1%
 
19583< 0.1%
 
19601< 0.1%
 
19613< 0.1%
 
ValueCountFrequency (%) 
201944342.7%
 
2018108526.7%
 
201774994.6%
 
201661393.8%
 
201575854.7%
 

tipo_envolvido
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Condutor
112035 
Passageiro
43241 
Pedestre
 
3708
Testemunha
 
3240
Cavaleiro
 
48
ValueCountFrequency (%) 
Condutor11203569.0%
 
Passageiro4324126.6%
 
Pedestre37082.3%
 
Testemunha32402.0%
 
Cavaleiro48< 0.1%
 
Não Informado1< 0.1%
 
2020-10-08T18:00:18.453417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-10-08T18:00:18.606323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:19.190959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length8
Mean length8.573200717
Min length8

estado_fisico
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Ileso
68634 
Lesões Leves
60500 
Lesões Graves
18573 
Não Informado
9233 
Óbito
 
5333
ValueCountFrequency (%) 
Ileso6863442.3%
 
Lesões Leves6050037.3%
 
Lesões Graves1857311.4%
 
Não Informado92335.7%
 
Óbito53333.3%
 
2020-10-08T18:00:19.414821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:19.576719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:19.815571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length12
Mean length8.980625243
Min length5

idade
Real number (ℝ≥0)

MISSING
SKEWED

Distinct122
Distinct (%)0.1%
Missing15759
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean39.87971115
Minimum0
Maximum2018
Zeros318
Zeros (%)0.2%
Memory size1.2 MiB
2020-10-08T18:00:20.049423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q127
median37
Q348
95-th percentile65
Maximum2018
Range2018
Interquartile range (IQR)21

Descriptive statistics

Standard deviation51.42658978
Coefficient of variation (CV)1.289542685
Kurtosis1050.092838
Mean39.87971115
Median Absolute Deviation (MAD)10
Skewness29.83797844
Sum5842936
Variance2644.694137
MonotocityNot monotonic
2020-10-08T18:00:20.294271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3840132.5%
 
3738592.4%
 
3238562.4%
 
3338512.4%
 
3638282.4%
 
3038142.4%
 
3437992.3%
 
3537812.3%
 
3137812.3%
 
2637012.3%
 
Other values (112)10823166.7%
 
(Missing)157599.7%
 
ValueCountFrequency (%) 
03180.2%
 
13270.2%
 
23080.2%
 
33130.2%
 
43370.2%
 
ValueCountFrequency (%) 
201851< 0.1%
 
20172< 0.1%
 
19191< 0.1%
 
191812< 0.1%
 
19083< 0.1%
 

sexo
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Masculino
114781 
Feminino
37155 
Não Informado
 
9233
Ignorado
 
1104
ValueCountFrequency (%) 
Masculino11478170.7%
 
Feminino3715522.9%
 
Não Informado92335.7%
 
Ignorado11040.7%
 
2020-10-08T18:00:20.557110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:20.711015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:20.928878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length9
Mean length8.991822423
Min length8

ilesos
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
0
93639 
1
68634 
ValueCountFrequency (%) 
09363957.7%
 
16863442.3%
 
2020-10-08T18:00:21.077784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
0
101773 
1
60500 
ValueCountFrequency (%) 
010177362.7%
 
16050037.3%
 
2020-10-08T18:00:21.166730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
0
143700 
1
18573 
ValueCountFrequency (%) 
014370088.6%
 
11857311.4%
 
2020-10-08T18:00:21.253676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mortos
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
0
156940 
1
 
5333
ValueCountFrequency (%) 
015694096.7%
 
153333.3%
 
2020-10-08T18:00:21.339623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

latitude
Categorical

HIGH CARDINALITY

Distinct37312
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
-27,59193546
 
211
-8,766685
 
184
-27,61000542
 
157
-5,089569
 
153
-27,63697369
 
152
Other values (37307)
161416 
ValueCountFrequency (%) 
-27,591935462110.1%
 
-8,7666851840.1%
 
-27,610005421570.1%
 
-5,0895691530.1%
 
-27,636973691520.1%
 
-27,603279791510.1%
 
-3,769990351470.1%
 
-27,6003841360.1%
 
-20,217404961330.1%
 
-27,644431230.1%
 
Other values (37302)16072699.0%
 
2020-10-08T18:00:21.631442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7691 ?
Unique (%)4.7%
2020-10-08T18:00:21.884283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length11
Mean length10.86825904
Min length2

longitude
Categorical

HIGH CARDINALITY

Distinct37317
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
-48,61824557
 
211
-63,884052
 
184
-48,63895057
 
157
-42,802288
 
153
-48,66514142
 
152
Other values (37312)
161416 
ValueCountFrequency (%) 
-48,618245572110.1%
 
-63,8840521840.1%
 
-48,638950571570.1%
 
-42,8022881530.1%
 
-48,665141421520.1%
 
-48,632018181510.1%
 
-38,670062821470.1%
 
-48,5997051360.1%
 
-40,269905781330.1%
 
-48,670571230.1%
 
Other values (37307)16072699.0%
 
2020-10-08T18:00:22.252056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique7679 ?
Unique (%)4.7%
2020-10-08T18:00:22.493906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length12
Mean length11.05523408
Min length3

regional
Categorical

HIGH CORRELATION

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
SR-MG
21350 
SR-SC
19656 
SR-PR
18162 
SR-RS
11444 
SR-RJ
10881 
Other values (23)
80780 
ValueCountFrequency (%) 
SR-MG2135013.2%
 
SR-SC1965612.1%
 
SR-PR1816211.2%
 
SR-RS114447.1%
 
SR-RJ108816.7%
 
SR-SP102106.3%
 
SR-BA87705.4%
 
SR-ES65814.1%
 
SR-PE65164.0%
 
SR-DF54273.3%
 
Other values (18)4327626.7%
 
2020-10-08T18:00:22.724762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-08T18:00:22.955619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length5
Mean length5.000394397
Min length5

delegacia
Categorical

HIGH CARDINALITY

Distinct173
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
DEL7/1
 
7196
DEL8/4
 
5655
DEL8/1
 
4696
DEL4/1
 
4398
DEL7/7
 
4299
Other values (168)
136029 
ValueCountFrequency (%) 
DEL7/171964.4%
 
DEL8/456553.5%
 
DEL8/146962.9%
 
DEL4/143982.7%
 
DEL7/742992.6%
 
DEL11/134792.1%
 
DEL5/129051.8%
 
DEL8/325611.6%
 
DEL16/124031.5%
 
DEL723631.5%
 
Other values (163)12231875.4%
 
2020-10-08T18:00:23.244440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-10-08T18:00:23.499278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length6
Mean length6.405526489
Min length2

uop
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct86
Distinct (%)0.1%
Missing8519
Missing (%)5.2%
Memory size1.2 MiB
UOP01/MG
 
9394
UOP01/SC
 
7524
UOP01/SP
 
6289
UOP02/MG
 
5871
UOP01/BA
 
5844
Other values (81)
118832 
ValueCountFrequency (%) 
UOP01/MG93945.8%
 
UOP01/SC75244.6%
 
UOP01/SP62893.9%
 
UOP02/MG58713.6%
 
UOP01/BA58443.6%
 
UOP01/RS56313.5%
 
UOP03/MG51943.2%
 
UOP01/ES50913.1%
 
UOP02/SC47883.0%
 
UOP03/SC46602.9%
 
Other values (76)9346857.6%
 
(Missing)85195.2%
 
2020-10-08T18:00:23.764116image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-10-08T18:00:24.009965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length8
Mean length7.737362346
Min length2

Interactions

2020-10-08T17:59:44.316634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:44.605454image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:44.937249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:45.213079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:45.508895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:46.337378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:46.625203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:46.923015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:47.281791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:47.588602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:47.923395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:48.252190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:48.577988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:48.848819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:49.154628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:49.428458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:49.727271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:50.011096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:50.308912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:50.606725image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:50.939519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:51.246328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:51.578122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:51.893927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:52.222723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:52.506546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:52.820349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:53.111170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:53.459953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:53.780755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:54.133533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:54.429350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:54.754148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:55.083945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:55.444720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T17:59:55.787504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-10-08T18:00:24.220832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-10-08T18:00:24.592602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-10-08T18:00:24.964372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-10-08T18:00:25.391105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-10-08T18:00:26.039702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-10-08T17:59:57.128672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:02.356421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:03.981412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-08T18:00:04.673983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

idpesiddata_inversadia_semanahorarioufbrkmmunicipiocausa_acidentetipo_acidenteclassificacao_acidentefase_diasentido_viacondicao_metereologicatipo_pistatracado_viauso_soloid_veiculotipo_veiculomarcaano_fabricacao_veiculotipo_envolvidoestado_fisicoidadesexoilesosferidos_levesferidos_gravesmortoslatitudelongituderegionaldelegaciauop
0182256.0403856.02019-01-01terça-feira04:00:00CE116.0136,9RUSSASAnimais na PistaAtropelamento de AnimalSem VítimasAmanhecerDecrescenteVentoSimplesCurvaNão324937CaminhãoI/MB 15SPRINT RONTAN AMB2012.0CondutorIleso35.0Masculino1000-4,766018-38,056034SR-CEDEL16/3UOP01/CE
1182263.0402859.02019-01-01terça-feira05:00:00MT158.0599,5AGUA BOADefeito Mecânico no VeículoIncêndioSem VítimasAmanhecerDecrescenteGaroa/ChuviscoSimplesRetaNão324940CaminhãoFORD/CARGO 815 N2011.0CondutorIleso30.0Masculino1000-14,319-52,169SR-MTDEL2/8UOP02/MT
2182277.0402850.02019-01-01terça-feira10:00:00PA10.034DOM ELISEUVelocidade IncompatívelColisão traseiraSem VítimasPleno diaDecrescenteNubladoSimplesNão InformadoNão324958Caminhão-tratorVOLVO/FH 540 6X4T2012.0CondutorIleso54.0Masculino1000-4,15296734-47,54608154SR-PADEL19/2UOP03/PA
3182289.0402431.02019-01-01terça-feira08:30:00BA101.013RIO REALIngestão de ÁlcoolColisão traseiraCom Vítimas FeridasPleno diaDecrescenteCéu ClaroDuplaDesvio TemporárioNão324987Caminhão-tratorSCANIA/R 440 A6X22018.0CondutorIleso43.0Masculino1000-11,5896-37,8761SR-SEDEL20/2UOP03/SE
4182307.0402642.02019-01-01terça-feira13:50:00BA116.0440FEIRA DE SANTANAIngestão de ÁlcoolSaída de leito carroçávelCom Vítimas FeridasPleno diaDecrescenteCéu ClaroDuplaCurvaNão325030Caminhão-tratorVOLVO/FH12 380 4X2T2003.0PassageiroLesões Graves37.0Masculino0010-12,344-39,087SR-BADEL10/2UOP01/BA
5182307.0402638.02019-01-01terça-feira13:50:00BA116.0440FEIRA DE SANTANAIngestão de ÁlcoolSaída de leito carroçávelCom Vítimas FeridasPleno diaDecrescenteCéu ClaroDuplaCurvaNão325030Caminhão-tratorVOLVO/FH12 380 4X2T2003.0CondutorLesões Leves57.0Masculino0100-12,344-39,087SR-BADEL10/2UOP01/BA
6182316.0402361.02019-01-01terça-feira15:15:00RS101.08TORRESFalta de Atenção à ConduçãoTombamentoSem VítimasPleno diaCrescenteCéu ClaroDuplaRetaSim325039Caminhão-tratorSCANIA/R124 GA6X4NZ 4202004.0CondutorIleso28.0Masculino1000-29,360483-49,807865SR-RSDEL9/3UOP03/RS
7182334.0402401.02019-01-01terça-feira14:45:00SE101.076,7MARUIMFalta de Atenção à ConduçãoSaída de leito carroçávelCom Vítimas FeridasPleno diaCrescenteSolSimplesRetaNão325068CaminhãoIVECO/TECTOR 240E252010.0CondutorNão InformadoNaNNão Informado0000-10,7853-37,1421SR-SEDEL20/1UOP01/SE
8182361.0402521.02019-01-01terça-feira10:00:00MG251.0280SALINASUltrapassagem IndevidaSaída de leito carroçávelCom Vítimas FeridasPleno diaDecrescenteSolSimplesRetaNão325052Caminhão-tratorVOLVO/FH 440 6X2T2011.0CondutorLesões Leves52.0Masculino0100-16,12498503-42,22251892SR-MGDEL4/11UOP02/MG
9182362.0404322.02019-01-01terça-feira18:20:00PE101.041IGARASSUIngestão de ÁlcoolColisão lateralSem VítimasPlena NoiteCrescenteCéu ClaroDuplaRetaSim325208CaminhãoVW/8.1401999.0CondutorIleso59.0Masculino1000-7,837-34,9124SR-PEDEL11/1UOP02/PE

Last rows

idpesiddata_inversadia_semanahorarioufbrkmmunicipiocausa_acidentetipo_acidenteclassificacao_acidentefase_diasentido_viacondicao_metereologicatipo_pistatracado_viauso_soloid_veiculotipo_veiculomarcaano_fabricacao_veiculotipo_envolvidoestado_fisicoidadesexoilesosferidos_levesferidos_gravesmortoslatitudelongituderegionaldelegaciauop
162263266158.0593481.02019-01-15terça-feira05:00:00AC364.0130RIO BRANCODefeito na ViaQueda de ocupante de veículoCom Vítimas FeridasAmanhecerCrescenteIgnoradoDuplaRetaSim474988MotocicletaHONDA/CG 150 TITAN ESD2013.0CondutorLesões GravesNaNMasculino0010-10,0131571-67,7137847SR-ACUOP01/ACNaN
162264266255.0593651.02019-10-07segunda-feira09:10:00ES101.0270,5SERRAFalta de Atenção à ConduçãoTombamentoCom Vítimas FeridasPleno diaCrescenteCéu ClaroDuplaRetaSim475144MotocicletaHONDA/CB 300R2015.0CondutorLesões GravesNaNMasculino0010-20,23106874-40,27387446SR-ESDEL12/2UOP01/ES
162265266255.0593652.02019-10-07segunda-feira09:10:00ES101.0270,5SERRAFalta de Atenção à ConduçãoTombamentoCom Vítimas FeridasPleno diaCrescenteCéu ClaroDuplaRetaSim475146OutrosNaNNaNCondutorIlesoNaNIgnorado1000-20,23106874-40,27387446SR-ESDEL12/2UOP01/ES
162266266406.0593905.02019-11-25segunda-feira07:20:00PR116.0125FAZENDA RIO GRANDEFalta de Atenção à ConduçãoColisão lateralCom Vítimas FeridasPleno diaDecrescenteCéu ClaroDuplaRetaSim475372Micro-ônibusNaNNaNCondutorNão InformadoNaNNão Informado0000-25,59505309-49,31630659SR-PRDEL7/1UOP03/PR
162267266406.0593903.02019-11-25segunda-feira07:20:00PR116.0125FAZENDA RIO GRANDEFalta de Atenção à ConduçãoColisão lateralCom Vítimas FeridasPleno diaDecrescenteCéu ClaroDuplaRetaSim475370MotocicletaHONDA/CG 150 TITAN KS2006.0PassageiroIleso25.0Masculino1000-25,59505309-49,31630659SR-PRDEL7/1UOP03/PR
162268266406.0593902.02019-11-25segunda-feira07:20:00PR116.0125FAZENDA RIO GRANDEFalta de Atenção à ConduçãoColisão lateralCom Vítimas FeridasPleno diaDecrescenteCéu ClaroDuplaRetaSim475370MotocicletaHONDA/CG 150 TITAN KS2006.0CondutorLesões Leves44.0Masculino0100-25,59505309-49,31630659SR-PRDEL7/1UOP03/PR
162269266434.0593948.02019-06-03segunda-feira19:00:00CE222.01,4CAUCAIANão guardar distância de segurançaColisão traseiraCom Vítimas FeridasPlena NoiteCrescenteCéu ClaroDuplaRetaSim475416AutomóvelFIAT/UNO MILLE WAY ECON2009.0CondutorLesões Graves41.0Masculino0010-3,736507-38,65337SR-CEDEL16/1UOP01/CE
162270266434.0593947.02019-06-03segunda-feira19:00:00CE222.01,4CAUCAIANão guardar distância de segurançaColisão traseiraCom Vítimas FeridasPlena NoiteCrescenteCéu ClaroDuplaRetaSim475415AutomóvelVW/GOLF 1.6 SPORTLINE2011.0CondutorIleso36.0Masculino1000-3,736507-38,65337SR-CEDEL16/1UOP01/CE
162271266573.0594270.02019-07-13sábado19:35:00PR373.0425CANDOIDefeito Mecânico no VeículoSaída de leito carroçávelCom Vítimas FeridasPlena NoiteDecrescenteIgnoradoSimplesRetaNão475680AutomóvelVW/VOYAGE 1.6NaNCondutorLesões GravesNaNMasculino0010-25,71180139-52,18373987SR-PRDEL7/3UOP02/PR
162272266627.0594393.02019-10-22terça-feira20:20:00BA324.0608SIMOES FILHODefeito na ViaQueda de ocupante de veículoCom Vítimas FeridasPlena NoiteCrescenteCéu ClaroSimplesRetaNão475775MotocicletaYAMAHA/MT032016.0CondutorLesões LevesNaNMasculino0100-12,78155812-38,41655733SR-BADEL10/1UOP01/BA